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James S. Castle, M.D.

James S. Castle, M.D.

James S. Castle, M.D.

Neurology
  • Locations
    Locations
    A

    NorthShore Medical Group

    757 Park Ave. West
    Suite 2850
    Highland Park, IL 60035
    847.570.2570 847.570.2073 fax
    View Map: Google
    This location is wheelchair accessible.
    B

    NorthShore Medical Group

    920 Milwaukee Ave.
    Suite 2100
    Lincolnshire, IL 60069
    847.570.2570 847.570.2073 fax
    View Map: Google
    This location is wheelchair accessible.
    C

    NorthShore Medical Group

    9650 Gross Point Rd.
    Suite 3900
    Skokie, IL 60076
    847.570.2570 847.570.2073 fax
    View Map: Google
    This location is wheelchair accessible.
  • Publications
    Publications

    • Building of EMR Tools to Support Quality and Research in a Memory Disorders Clinic.

      Frontiers in neurology 2019

      Authors: Simon KC, Yucus C, Castle J, Chesis R, Lai R, Hillman L, Tideman S, Garduno L, Meyers S, Frigerio R, Maraganore DM
      Abstract
      The electronic medical record (EMR) presents an opportunity to standardize patient data collection based on quality guidelines and conduct practice-based research. We describe the development of a customized EMR "toolkit" that standardizes patient data collection with hundreds of discrete fields that supports Best Practices for treating patients with memory disorders. The toolkit also supports practice-based research. We describe the design and successful implementation of a customized EMR toolkit to support Best Practices in the care of patients with memory disorders. We discuss applications, including quality improvement projects and current research initiatives, using the toolkit. This toolkit is being shared with other departments of Neurology as part of the Neurology Practice-Based Research Network. Data collection is ongoing, including longitudinal follow-up. This toolkit will generate data that will allow for descriptive and hypothesis driven research as well-quality improvement among patients seen in a memory clinic.
      PMID: 30899241 [PubMed - as supplied by publisher]

    • Design and implementation of pragmatic clinical trials using the electronic medical record and an adaptive design.

      JAMIA open 2018 Jul

      Authors: Simon KC, Tideman S, Hillman L, Lai R, Jathar R, Ji Y, Bergman-Bock S, Castle J, Franada T, Freedom T, Marcus R, Mark A, Meyers S, Rubin S, Semenov I, Yucus C, Pham A, Garduno L, Szela M, Frigerio R, Maraganore DM
      Abstract
      To demonstrate the feasibility of pragmatic clinical trials comparing the effectiveness of treatments using the electronic medical record (EMR) and an adaptive assignment design.
      We have designed and are implementing pragmatic trials at the point-of-care using custom-designed structured clinical documentation support and clinical decision support tools within our physician's typical EMR workflow. We are applying a subgroup based adaptive design (SUBA) that enriches treatment assignments based on baseline characteristics and prior outcomes. SUBA uses information from a randomization phase (phase 1, equal randomization, 120 patients), to adaptively assign treatments to the remaining participants (at least 300 additional patients total) based on a Bayesian hierarchical model. Enrollment in phase 1 is underway in our neurology clinical practices for 2 separate trials using this method, for migraine and mild cognitive impairment (MCI).
      We are successfully collecting structured data, in the context of the providers' clinical workflow, necessary to conduct our trials. We are currently enrolling patients in 2 point-of-care trials of non-inferior treatments. As of March 1, 2018, we have enrolled 36% of eligible patients into our migraine study and 63% of eligible patients into our MCI study. Enrollment is ongoing and validation of outcomes has begun.
      This proof of concept article demonstrates the feasibility of conducting pragmatic trials using the EMR and an adaptive design.
      The demonstration of successful pragmatic clinical trials based on a customized EMR and adaptive design is an important next step in achieving personalized medicine and provides a framework for future studies of comparative effectiveness.
      PMID: 30386852 [PubMed - as supplied by publisher]

    • Agreement regarding diagnosis of transient ischemic attack fairly low among stroke-trained neurologists.

      Stroke 2010 Jul

      Authors: Castle J, Mlynash M, Lee K, Caulfield AF, Wolford C, Kemp S, Hamilton S, Albers GW, Olivot JM
      Abstract
      Agreement between physicians to define the likelihood of a transient ischemic attack (TIA) remains poor. Several studies have compared neurologists with nonneurologists, and neurologists among themselves, but not between fellowship-trained stroke neurologists. We investigated the diagnostic agreement in 55 patients with suspected TIA.
      The history and physical examination findings of 55 patients referred to the Stanford TIA clinic from the Stanford emergency room were blindly reviewed by 3 fellowship-trained stroke neurologists who had no knowledge of any test results or patient outcomes. Each patient's presentation was rated as to the likelihood that the presentation was consistent with TIA. We used 3 different scales (2-, 3-, and 4-point scales) to define TIA likelihood. We assessed global agreement between the raters and evaluated the biases related to individual raters and scale type.
      The agreement between fellowship-trained stroke neurologists remained poor regardless of the rating system used and the statistical test used to measure it. Difference in rating bias among all raters was significant for each scale: P=0.001, 0.012, and <0.001. In addition, for each reviewer, the rate of labeling an event an "unlikely TIA" progressively decreased with the number of points that composed the scale.
      TIA remains a highly subjective diagnosis, even among stroke subspecialists. The use of confirmatory testing beyond clinical judgment is needed to help solidify the diagnosis. Caution should be used when diagnosing an event as a possible TIA.
      PMID: 20508192 [PubMed - as supplied by publisher]
    View more results at PubMed.gov
  • In the News
    In the News

    Oct 2013

  • Social Media
    Social Media